The present invention relates to video processing, and more particularly to a method of predicting subjective quality ratings of video from corresponding human vision model perceptual difference scores.
Although methods exist for producing perceptual difference scores that may correlate well under certain conditions with standard subjective quality ratings, such as Difference Mean Opinion Scores (DMSO), the actual numerical DMOS values depend among other things on xe2x80x9cbestxe2x80x9d (least impaired) and xe2x80x9cworstxe2x80x9d (most impaired) video training sequences used to calibrate human subjects doing the scoring. Subjects are told to use a scale with one end for the xe2x80x9cbestxe2x80x9d and the other for the xe2x80x9cworstxe2x80x9d video training sequence. Then video test sequences are rated by the subjects based on the xe2x80x9ccalibratedxe2x80x9d scale. However the scale of subjective ratings for the video test sequences inherently has a compression near the top and bottom as subjects are conservative with quality ratings at the extremes, reserving a little portion of the scale just in case a more extreme video quality is seen in a later video test sequence.
The existing methods of determining video picture quality, such as that described in U.S. Pat. No. 5,818,520 and implemented in the Tektronix Picture Quality Analyzer PQA200, do not attempt to match DMOS scales for a set of video sequences, such as by using xe2x80x9cbestxe2x80x9d and xe2x80x9cworstxe2x80x9d video training sequences to set the extremes. Instead correlations are made and typical conversion factors are cited. These typical conversion factors imply a one-to-one or linear mapping, not taking into account the compression at the extremes of the scale or other non-linearities inherent in the DMOS values.
What is desired is a picture quality measurement system that predicts subjective quality ratings of processed video.
Accordingly the present invention provides a method of predicting subjective quality ratings of processed video from corresponding human vision model perceptual difference scores by obtaining perceptual difference scores for a xe2x80x9cWorstxe2x80x9d quality video training sequence and for a xe2x80x9cBestxe2x80x9d quality video training sequence. Corresponding subjective quality rating values are assigned to the perceptual difference scores as modified by any single-ended measures of impairments that may exist in the reference video training sequences from which the xe2x80x9cWorstxe2x80x9d and xe2x80x9cBestxe2x80x9d quality video training sequences are derived. A conversion function, which may be a piecewise linear function, an xe2x80x9cSxe2x80x9d curve function or other function that approximates the non-linearities and compression at the extremes of the subjective quality rating scale, is used to produce a conversion curve of calibration values based on the perceptual difference scores for the xe2x80x9cWorstxe2x80x9d and xe2x80x9cBestxe2x80x9d quality video training sequences and heuristically derived constants.
The objects, advantages and other novel features of the present invention are apparent from the following detailed description when read in conjunction with the appended claims and attached drawing.